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1
Maximizing Throughput of Aerial Base Stations via Resources..:
, In:
2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)
,
Park, Yu Min
;
Hassan, Sheikh Salman
;
Hong, Choong Seon
- p. 1-4 , 2022
Link:
https://doi.org/10.23919/APNOMS56106.2022.9919980
RT T1 <cTitle>2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)</cTitle>: T1 <Title>Maximizing Throughput of Aerial Base Stations via Resources-based Multi-Agent Proximal Policy Optimization: A Deep Reinforcement Learning Approach</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9919980&Exemplar=1&LAN=DE A1 Park, Yu Min A1 Hassan, Sheikh Salman A1 Hong, Choong Seon YR 2022 K1 Wireless communication K1 Base stations K1 Rain K1 Simulation K1 Reinforcement learning K1 Throughput K1 Autonomous aerial vehicles K1 Unmanned aerial vehicle K1 millimeter wave K1 multi-agent deep reinforcement learning K1 balanced k-means clustering K1 proximal policy optimization SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.23919/APNOMS56106.2022.9919980 DO https://doi.org/10.23919/APNOMS56106.2022.9919980 SF ELIB - SuUB Bremen
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